• Korean Journal of Medicinal Crop Science
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• v.2 no.2
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• pp.140-145
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• 1994

B. falcatum plants were classified into six groups from group I to grop VI by the complete linkage cluster method depending on 8 charactenstics such as plant height. number of nodes, number of branches, position of the first branching node root diameter, root length, number of lateral root, dry weight of root. These groups are divided into two plants types, such as multi-branching and non multi-branching type by the number of branches, group II and group VI were the multi-branching types and the other groups were nonmulti-branching ones, Dry weight of root had highly positive correlation with the number of branches and negative correlation with the position of first branching nodes.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.44 no.2
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• pp.166-170
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• 1999

The identification of quantitative trait loci (QTL) has the potential to enhance the efficiency of im- proving food processing traits of soybean. In this study, 92 restriction fragment length polymorphism (RFLP) loci and two morphological markers (W$_1$ and T) were used to identify QTL associated with food processing traits of soybean for sprout in 83 F$_2$-derived lines from a cross of ＇Pureun＇ x ＇Jinpum 2＇. The genetic map consisted of 76 loci which covered about 760 cM and converged into 20 linkage groups. Eighteen markers remained unlinked. Phenotypic data were collected for hypocotyl length, abnormal seedling rate, and sprout yield seven days after seed germination at 2$0^{\circ}C$. Based on the single-factor analysis of variance, eight independent markers were associated with hypocotyl length. Four of seven markers associated with abnormal seedling rate were identified as independent. Seven loci were associated with sprout yield. For three different traits, much of genetic variation was explained by the identified QTL in this population. Several RFLP markers in linkage group (LG) Bl were detected as being associated with three traits, providing a genetic explanation for the biological correlation of sprout yield with hypocotyl length (r=OA07＊＊＊) and with abnormal seedling rate (r=-406＊＊＊).

• Journal of Animal Science and Technology
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• v.54 no.6
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• pp.463-469
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• 2012

This study utilized a standardization and cluster analysis technique for the selection and classification of beneficial bacteria. A set of synthetic data consisting of 100 individual variables with three characteristics was created for analysis. The three characteristics assigned to each independent variable were designated to have different numeric scales, averages, and standard deviations. The variables were bacterial isolates at random, and the three characteristics were fermentation products, including cell yield, antioxidant activity of culture, and enzyme production. A standardization method utilizing a standard normal distribution equation to record fermentation yields of each isolate was employed to weight their different numeric scales and deviations. Following transformation, the data set was analyzed by cluster analysis. The Manhattan method for dissimilarity matrix construction along with complete linkage technique, an agglomerative method for hierarchical cluster analysis, was employed using statistical computing program R. A total of 100 isolates were classified into groups A, B, and C. In a comparison of the characteristics of each group, all characteristics in groups A and C were higher than those of group B. Isolates displaying higher cell yield were classified as group A, whereas those isolates showing high antioxidant activity and enzyme production were assigned to group C. The results of the cluster analysis can be useful for the classification of numerous isolates and the preparation of an isolation pool using numerical or statistical tools. The present study suggests that a simple technique can be applied to screen and select beneficial microbes using the freely downloadable statistical computing program R.

• Proceedings of the Korean Society of Life Science Conference
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• 2002.12a
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• pp.13-19
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• 2002

To elucidate the regulatory mechanism for expression of sialyl-glycoconjugates and their biological functions, ninetheen sialyltransferase cDNAs including eleven by our group or co-works have been cloned and characterized so far. The cloned sialyltransferases are classified into four families according to the carbohydrate linkages they synthesize: ${\alpha}2,3-sialyltransferase$ (ST3Gal I-VI), ${\alpha}$ 2,6-sialyltransferase (ST6Gal I), GalNAc ${\alpha}$ 2,6-sialyltransferase (ST6GalNAc I-VI), and ${\alpha}2,8-sialyltransferase$ (ST8Sia I-VI). Each of the sialyltransferase genes is differentially expressed in a tissue-, cell type-, and stage-specific manner. These enzymes differ in their substrate specificity and various biochemical parameters. However, enzymatic analysis conducted in vitro with recombinant enzyme revealed that one linkage can be synthesized by multiple enzymes. We present here an overview of structure and function of sialyltransferases performed by our group and co-works. Genomic structures and transcriptional regulation of two kinds of human sialyltransferase gene are also presented.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.28 no.3
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• pp.340-344
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• 1983

Taxonomic distances and Q correlations of all possible comparisons among thirty-two collected soybean varieties were calculated from the standardized mean of twenty-one characters. Ten varietal groups were classified by the single linkage clustering based on Q correlations. The means of Q correlations of intra-group were higher than those of inter-group. Each groups were characteristic in each mean of characters within varietal groups.

• Journal of Information Technology Services
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• v.6 no.3
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• pp.141-162
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• 2007

In this study, we conduct a case analysis on EZmedicom which is one of the leading companies in e-Marketplace for medical fields. By examining major business models of EZmedicom, we provide the success factors in launching the electronic commerce to the potential companies which are interested in participating in e-marketplace for medical fields. Especially, we deduct the solution, logistics field, and electronic group-purchasing as its major business model. Based on these factors, we also propose the MDvan solution which is one of the electronic purchase and supply system, Ezlogis that is the system supporting logistics parts in medical fields, VMI(vendor management inventory), standardization of item code and the linkage of SCM as its critical success factors of EZmedicom. The findings of this study suggest practical and managerial implications for e-Marketplace implementation in the medical field and further research.

• Journal of Korean Society of Forest Science
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• v.112 no.1
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• pp.40-56
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• 2023

Tree species within the Populus genus grow rapidly and have an excellent capacity to absorb carbon, conferring substantial ability to effective purify the environment. Poplar breeding can be achieved rapidly and efficiently if a genetic linkage map is constructed and quantitative trait loci (QTLs) are identified. Here, a high-density genetic linkage map was constructed for the control pollinated progeny using the genotyping-by-sequencing (GBS) technique, which is a next-generation sequencing method. A search was also performed for the genes associated with quantitative traits located in the genetic linkage map by examining the variables of height and diameter at root collar, and resilience to insect damage. The height and diameter at root collar were measured directly, while the ability to recover from insect damage was scored in a 4-year-old breeding population of aspen hybrids (Odae19 × Bonghyeon4 F1) established in the research forest of Seoul National University. After DNA extraction, paternity was confirmed using five microsatellite markers, and only the individuals for which paternity was confirmed were used for the analysis. The DNA was cut using restriction enzymes and the obtained DNA fragments were prepared using a GBS library and sequenced. The analyzed results were sorted using Populus trichocarpa as a reference genome. Overall, 58,040 aligned single-nucleotide polymorphism (SNP) markers were identified, 17,755 of which were used for mapping genetic linkages. The genetic linkage map was divided into 19 linkage groups, with a total length of 2,129.54 cM. The analysis failed to identify any growth-related QTLs, but a gene assumed to be related to recovery from insect damage was identified on linkage group (chromosome) 4 through genome-wide association study.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.49 no.5
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• pp.429-433
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• 2004

A single recessive gene, rxp, controls the bacterial leaf pustule (BLP) resistance in soybean and in our previous article, it has been mapped on linkage group (LG) D2 of molecular genetic map of soybean. A total of 130 recombinant inbred lines (RILs) from a cross between BLP-resistant SS2-2 and BLP-susceptible Jangyeobkong were used to identify molecular markers linked to rxp. Fifteen simple sequence repeat (SSR) markers on LG D2 were screened to construct a genetic map of rxp locus. Only four SSR markers, Satt135, Satt372, Satt448, and Satt486, showed parental polymorphisms. Using these markers, genetic scaffold map was constructed covering 26.2cM. Based on the single analysis of variance, Satt372 among these four SSR markers was the most significantly associated with the resistance to BLP. To develop new amplified fragment length polymorphism (AFLP) marker linked to the resistance gene, bulked segregant analysis (BSA) was employed. Resistance and susceptible bulks were made by pooling equal amount of genomic DNAs from ten of each in the segregating population. A total of 192 primer combinations were used to identify specific bands to the resistance, selecting three putative AFLP markers. These AFLP markers produced the fragment present in SS2-2 and the resistant bulk, and not in Jangyeobkong and the susceptible bulk. Linkage analysis revealed that McctEact97 $(P=0.0004,\;R^2=14.67\%)$ was more significant than Satt372, previously reported as the most closely linked marker.

• Korean Journal of Medicinal Crop Science
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• v.5 no.4
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• pp.260-265
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• 1997

Varietal distances were measured by Euclidian $D^2$ statistics in 1, 891 possible comparisons among sixty two varieties of Alisma plantago with seven characters such as leaf width, leaf length, stem length, number of stems per plant, root diameter, and yield of fresh and dry root. A complete linkage cluster analysis based on the Euclidian distance $(D^2)$ was attempted. Sixty two cultivars of Alisma plantago were largely classified into five subgroups. Group 1, 2, 3, 4 and 5 included twelve, twenty one, seventeen, five and seven cultivars, respectively. Most of the varietal groups were not associated with their geographical origins. Stem length and root weight among the seven characters were the largest contributors to the $D^2$ in both intra- and inter- groups.

• Proceedings of the Korean Society of Crop Science Conference
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• 2022.10a
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• pp.233-233
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• 2022

As the world's population grows and food needs diversify, the demand for horticultural crops for beneficial traits is increasing. In order to meet this demand, it is necessary to develop suitable cultivars and breeding methods accordingly. Breeding methods have changed over time. With the recent development of sequencing technology, the concept of genomic selection (GS) has emerged as large-scale genome information can be used. GS shows good predictive ability even for quantitative traits by using various markers, breaking away from the limitations of Marker Assisted Selection (MAS). Moreover, GS using machine learning (ML) and deep learning (DL) has been studied recently. In this study, we aim to build a system that selects phenotype-related markers using the genomic information of the pepper population and trains a genomic selection model to select individuals from the validation population. We plan to establish an optimal genome wide association analysis model by comparing and analyzing five models. Validation of molecular markers by applying linkage markers discovered through genome wide association analysis to breeding populations. Finally, we plan to establish an optimal genome selection model by comparing and analyzing 12 genome selection models. Then We will use the genome selection model of the learning group in the breeding group to verify the prediction accuracy and discover a prediction model.